1. Field of the Invention
The present invention relates generally to digital subscriber line (DSL) systems. More particularly, the present invention relates to characterization of impulse noise.
2. Related Art
High-bandwidth systems, including DSL systems use single-carrier modulation as well as multi-carrier modulation schemes. Both DSL and other high-bandwidth systems such as wireless use modulation schemes such as Carrier-less Amplitude and Phase modulation (CAP) and Discrete Multi-tone (DMT) for wired media and Orthogonal Frequency Division Multiplexing (OFDM) for wireless communication. One advantage of such schemes is that they are suited for high-bandwidth application of 2 Mbps or higher upstream (subscriber to provider) and 8 Mbps or higher downstream (provider to subscriber). Quadrature Amplitude Modulation (QAM) utilizes quadrature keying to encode more information on the same frequency by employing waves in the same frequency shifted by 90°, which can be thought of as sine and cosine waves of the same frequency. Since the sine and cosine waves are orthogonal, data can be encoded in the amplitudes of the sine and cosine waves. Therefore, twice as many bits can be sent over a single frequency using the quadrature keying. QAM modulation has been used in voice-band modem specifications, including the V.34.
CAP is similar to QAM. For transmission in each direction, CAP systems use two carriers of identical frequency above the 4 kHz voice band, one shifted 90° relative to the other. CAP also uses a constellation to encode bits at the transmitter and decode bits at the receiver. A constellation encoder maps a bit pattern of a known length to a sinusoid wave of a specified magnitude and phase. Conceptually, a sinusoidal wave can be viewed to be in one-to-one correspondence with a complex number where the phase of the sinusoidal is the argument (angle) of the complex number, and the magnitude of the sinusoidal wave is the magnitude of the complex number, which in turn can be represented as a point on a real-imaginary plane. Points on the real-imaginary plane can have bit patterns associated with them, and this is referred to as a constellation and is known to one of ordinary skill in the art.
DMT modulation, sometimes called OFDM, builds on some of the ideas of QAM but, unlike QAM, it uses more than one constellation encoder where each encoder receives a set of bits that are encoded and outputs sinusoid waves of varying magnitudes and phases. However, different frequencies are used for each constellation encoder. The outputs from these different encoders are summed together and sent over a single channel for each direction of transmission. For example, common DMT systems divide the spectrum from 0 kHz to 1104 kHz into 256 narrow channels called tones (sometimes referred to as bins, DMT tones or sub-channels). These tones are 4.3125 kHz wide. The waveforms in each tone are completely separable from one another. In order to maintain separability, the frequencies of the sinusoidal used in each tone should be multiples of a common frequency known as the fundamental frequency and in addition the symbol period τ, must be a multiple of the period of the fundamental frequency or a multiple thereof. The aggregate bit pattern which comprises the bit patterns mapped to constellations in each of the tones during a symbol period is often referred to as a DMT symbol. For the purposes here, time is often referred to in terms of DMT symbols meaning a symbol period.
The presence of impulse noise can occur in digital subscriber line (xDSL) systems due to electromagnetic interference from such sources as a telephone network, power system, and even from natural phenomena such as thunderstorms and lightning. The presence of impulse noise can significantly limit the reliability of real-time services such as video that can be supported by current generation xDSL systems, for example, VDSL (Very High Speed DSL). The occurrence of impulse noise can cause severe degradation in the DMT symbols received. The degraded DMT symbols resulting from the impulse noise can cause physical layer cyclic redundancy code (CRC) errors and loss of packets in xDSL systems, thereby affecting such triple-play services as IPTV. Therefore, there has been substantial interest in the DSL community recently towards the development and standardization of impulse noise monitoring (INM) schemes.
In particular, the classification of impulse sources on a particular line is of great importance to the service provider so that the appropriate impulse noise protection (INP) approach can be taken. The typical classes of impulse noise observed on a line are repetitive electrical impulse noise (REIN), prolonged electrical impulse noise (PEIN), and a single high impulse noise event (SHINE). Electromagnetic interference from telephone networks, fluorescent lights, power supply units of TVs or PCs, video recorders, electronic transformers, etc. in the vicinity of a particular line, can cause noise impulses having a repetitive character often proportional to the frequency of the power lines (60 Hz in the U.S. and 50 Hz in Europe). This is an example of REIN. Lightning would be an example a source of SHINE. Certain household appliances often have a prolonged electrical interference and are periodic, i.e., are sources of PEIN.
In addition to the classification of noise, other critical information of importance to a service provider is the length and the inter-arrival time (IAT) of the impulse noise. These and other characteristics of impulse noise are illustrated in FIG. 1. FIG. 1 is an example of the impulse noise bursts (clusters) detected from an impulse noise sensor (INS). More precisely in general, an INS detects severely degraded DMT symbols, the effect of impulse noise, so even though language often is expressed as detecting or measuring impulse noise, in practicality, most INM approaches actually monitor severely degraded DMT symbols. The IAT is the number of data symbols from the start of an impulse noise cluster to the start of the next impulse noise cluster. If one or more sync symbols occur between two clusters, they shall not be counted in the IAT. More specifically, in FIG. 1, impulse 102, 104, and 106 are part of a first impulse noise cluster (CL1); impulse 108 comprises a second impulse noise cluster (CL2). The number of symbols between the start of the first impulse in a noise cluster and the end of the last impulse in a noise cluster is the impulse noise cluster length (INCL) as illustrated for the first impulse noise cluster. The number of degraded symbols in a given impulse noise cluster defines INCD. The number of gaps in the impulse noise clusters defines INCG. A cluster, per the VDSL2 standard (ITU G.993.2 Amendment 2, February 2008) as well as other standards, is defined by the impulse noise monitoring cluster continuation (INMCC) parameter. If two impulses are within INMCC they are considered part of the same cluster as indicated for impulses 102, 104, and 106. However, impulses 106 and 108 are separated by more than INMCC so they are not part of the same cluster.
Additionally according to the VDSL2 standard, the equivalent INP (INP_eq) should be calculated as a standard calculated value based on the INM_INPEQ_MODE parameter and can be dependent on the INMCC, INCL and/or INCD as given below. The VDSL2 standard specifies that the INMCC parameter can be provided as a central-office (CO) management information base (MIB) parameter and can have integer values from 0 and 64. Specifically, the equivalent INP is a quantity that can be used by the impulse noise protection system to better configure its impulse noise mitigation. For example, the equivalent INP could be the impulse noise cluster length so that a channel coding system such as a Reed-Solomon interleaving system can allocate enough redundant information to compensate for the impulse noise. The particulars of the desired equivalent INP can vary depending on the impulse noise protection scheme used. The standard defines a total measurement counter, INMAME, which is incremented whenever a data symbol is processed by the INS. In effect, the value of INMAME can be used to keep track of time. The standard also defines a histogram INMAINPEQ comprising histogram primitives INMAINPEQ1-17 which are incremented based on the INP_eq. For example, INMAINPEQi is incremented each time INP_eq=i, with the exception that INMAINPEQ17 is incremented when INP_eq>16. Another histogram defined by the standard is INMAIAT comprising histogram primitives INMAIAT0-7 which are incremented based on the IAT. It uses two parameters, the INM inter-arrival time offset (INMIATO), which can take on valid values of 3-511 and the INM inter-arrival time step (INMIATS) which can have valid values of 0-7. While the values of INMIATO and INMIATS have initial default values of 3 and 0, respectively, the standard does not describe any method for adjusting or optimizing these parameters.
FIG. 2 shows how the various INMAIATi histogram primitives are incremented. Since, in the minimum case, IAT value can only be as small as 2, INMAIAT0 range starts at 2. The range ends at INMIATO−1, making the range contain INMIATO−2 values. Histogram primitives INMAIAT1-6 divide up the next six regions equally so that they all have 2INMIATS values. Specifically, INMAIAT1 is incremented whenever an IAT value falls between INMATO and INMIATO+2INMIATS−1, INMAIAT2 is incremented whenever an IAT value falls between INMATO+2INMIATS and INMIATO+2×2INMIATS−1, INMAIAT3 is incremented whenever an IAT value falls between INMATO+2×2INMIATS and INMIATO+3×2INMIATS−1, INMAIAT4 is incremented whenever an IAT value falls between INMATO+3×2INMIATS and INMIATO+4×2INMIATS−1, INMAIAT5 is incremented whenever an IAT value falls between INMATO+4×2INMIATS and INMIATO+5×2INMIATS−1, and finally INMAIAT6 is incremented whenever an IAT value falls between INMATO+5×2INMIATS and INMIATO+6×2INMIATS−1. The counter INMAIAT7 is reserved to be incremented for any value of IAT greater still, that is, greater than INMIATO+6×2INMIATS.
In addition, the VDSL2 standard as well as others, such as the ADSL2+ standard are now requiring modems to have a built in capability of monitoring the impulse noise in the field. The standard dictates the method for deriving some standard INM parameters.
FIG. 3 shows a functional block diagram of an impulse noise monitor as prescribed by the standards. Impulse Noise Sensor 302 (INS) indicates whether a data symbol is severely degraded or not. The implementation details for this sensor are well known in the art. If a sync symbol occurs between two data symbols (severely degraded or not), INS 302 will disregard it.
Cluster indicator 306 indicates short groups of severely degraded data symbols as clusters. The cluster can contain a single severely degraded data symbol, a group of consecutive severely degraded data symbols, or several groups of one or more consecutive severely degraded data symbols with gaps between the groups. Cluster indicator 306 uses the following rule to identify the cluster. A gap is defined as a group of non-severely degraded data symbols in between two severely degraded data symbols. A cluster is defined as the largest group of consecutive data symbols, starting and ending with a severely degraded data symbols, containing severely degraded data symbols, separated by gaps smaller than or equal to INMCC as described above. As a consequence of the above definition of a cluster, each cluster starts with a severely degraded data symbol preceded by a gap larger than INMCC and ends with a severely degraded data symbol followed by a gap larger than INMCC, while gaps inside the cluster are all smaller than or equal to INMCC.
Eq INP generation block 308 is used to generate the “Equivalent INP” (i.e., the INP_eq described above) of the cluster as prescribed by the standard. It can use the INCL, INCD and INCG as calculated by cluster indicator 306. The generation is dependent on the mode selected by the parameter INM_INPEQ_MODE. If INM_INPEQ_MODE is zero then INP_eq is set to INCL, and INMCC is also set to zero irrespective of the CO MIB setting. If INM_INPEQ_MODE is one then INP_eq is also set to INCL with INMCC set to the CO MIB specified value. If INM_INPEQ_MODE is two then INP_eq is set to INCD with INMCC set to the CO MIB specified value. If INM_INPEQ_MODE is three then INP_eq is set using a set of equations related to interoperation with a Reed-Solomon coding as defined in the standard, specifically in Draft Amendment 2 to International Telecommunications Union (ITU-T), “Recommendation G.993.2, Very High Speed Digital Subscriber Line transceivers 2 (VDSL2)”, Section 11.4.2.2, pp. 15-20, 2007, henceforth referred to as “Draft Amendment 2,” which is hereby incorporated by reference. If INM_INPEQ_MODE is four, then INP_eq is essentially set to a vendor specified value.
In IAT generation block 310, the IAT is generated as the number of data symbols from the start of a cluster to the start of the next cluster. If sync symbols occur between two clusters, they shall not be counted in the IAT.
Block 312 generates anomalies for several ranges of IAT as described in FIG. 2 and appropriate INM counters 314 are incremented, specifically those that represent the IAT histogram. Furthermore, block 312 generates anomalies for several values of INP_eq as described above and appropriate INM counters 314 are incremented, specifically those that represent the INP_eq histogram. Finally, INM counters 314 further comprise the INMAME counter which is incremented for each data symbol encountered or processed by the INS.
What is currently lacking is a solution for processing the standard based INM parameters and primitives described above into information that is meaningful to the service provider, e.g., the length and the inter-arrival time of the impulse noise sources such as REIN. Such a method would be applicable to any modem running a standard compliant INM and would be of paramount importance. This shall aid to characterize the impulse noise occurring on the line so that the appropriate INP parameters could be chosen/tuned to ensure that physical layer CRC errors caused by the noise are corrected.
The INM procedure specifies the messaging protocol and the standard parameters which need to be calculated by the customer premises equipment (CPE). The CO acts as a master, and can set the parameters or read-out the calculated values using the INM facility command, which is a standard based mechanism to exchange INM commands between the CO and CPE and can set the values for INMIATO, INMIATS, INMCC and INM_INPEQ_MODE. The CPE is expected to use the set configuration by the CO and calculate all the parameters using a typical block diagram as shown in FIG. 3.
The previous solutions do not address the classification of the type of impulse noise occurring in the field and identify multiple REIN sources in xDSL INM. Moreover, no solution that we know of leverages the INM parameters and histogram primitives in the standards to ensure that the modems work satisfactorily against a wide array of impulses in the field. There are variations towards the impulse noise predictions which are captured below.
Bailey, et al, in U.S. Pat. No. 7,274,746 proposes an impulse noise mitigation based on the prediction of an impulse noise to carry out its mitigation. Schmidt, et al., in U.S. Pat. No. 7,263,174 proposes impulse noise mitigation based on a system to sum the number of counts to produce a rate for noise impulse. Both these approaches provide means to predict the performance of the line, but are not sufficient to tune the INP parameters.
Kerpez, et al, in U.S. Pat. No. 7,106,833 proposes yet another approach which provides a means to measure impulse noise by long-term (an hour or more) monitoring of raw bit errors, to enable identification of the impulse noise. However, there is no impulse noise classification involved and mere monitoring of impulse noise in long-term is not enough. Typically, not enough information is gathered to protect modems quickly against a wide array of impulse noises in the field.
Betts, et al, in U.S. Pat. No. 7,031,381, provides a method to reduce the number of bit errors that occur as a result of periodic transients in DSL data transmission by suspending or reducing data transmission during the occurrence of a subsequent transient. In this case, there is no mention of the INP tuning involved.
Khadavi, et al, in U.S. Pat. No. 7,027,405, proposes another approach based on the impulse noise counts in order to qualify the local loop for a particular DSL technology. Bremer, et al., in U.S. Pat. No. 6,885,730, proposes a method to count the occurrences per minute of impulse noise for testing the subscriber loop conditions. Again both these approaches fail to classify the type of impulse noise encountered.
There are numerous applications of time analysis used to detect and estimate signals in the signal processing context. For example, Chen, et al, in U.S. S.I.R. H001726 and Varshney et al (“Radar Signal Detection and Estimation Using Time-frequency Distributions,” Syracuse University, NY, October 1995) both use applications of time analysis in the field of radar. Liu, et al, (“Fundamental Frequency Estimation Based on the Joint Time-Frequency Analysis of Harmonic Spectral Structure,” IEEE Transactions of Speech and Audio processing, Vol. 9, No. 6, September 2001) use applications of time analysis in the field of speech. Papandreou, et al. (“Detection and Estimation of Generalized Chirps Using Time-frequency Representations,” Signals, Systems and Computers, 1994 Conference Record of the Twenty-Eighth Asilomar Conference, Volume 1, Issue, 31 Oct.-2 Nov. 1994 Page(s):50-54 vol. 1) use applications of time analysis on non-stationary signals such as chirp signals.
Finally, in a prior patent application U.S. application Ser. No. 12/098,696 entitled “Systems and Methods for Monitoring Impulse Noise” filed on Apr. 7, 2008 which is incorporated by reference herewith, a dual-speed detection and estimation approach to monitor impulse noise conditions on the line which adopts post processing based on non-standard histogram primitives is proposed.
Accordingly, various needs exist in the industry to address the aforementioned deficiencies and inadequacies.